As a system for recommending distribution information when distributing information such as contents, a “collaborative filtering” method is conventionally known (see Non-Patent Literature 1). The collaborative filtering is a method for estimating a user profile (what type the user belongs to, and the like) from the similarity of user history in the past and determining the next recommended item.
In Patent Literature 1, a method is described in which a preferred cluster and a non-preferred cluster are created by contents which a user viewed and contents which the user did not view, and contents are recommended in order from a content similar to the preferred cluster and not similar to the non-preferred cluster.    Patent Literature 1: Japanese Patent Application Laid-Open Publication No. 2008-210010    Non-Patent Literature 1: Toshiyuki Masui, “Interface no Machikado (Street Corner of Interface) (93)—Bookshelf Calculation” Unix Magazine, Vol. 20, No. 12, 2005